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Summary: A Multiprocessor Server-Based Scheduler for
Soft Real-Time Tasks with Stochastic Execution Demand
Alex F. Mills
Department of Statistics and Operations Research
University of North Carolina
James H. Anderson
Department of Computer Science
University of North Carolina
Abstract
We utilize a multiprocessor server-based approach to
schedule a general class of soft real-time systems with
stochastic execution demands, when bounded average-
case tardiness is sufficient for schedulability. A key fea-
ture of the task model considered here is that the stochas-
tic execution-time demands can have arbitrary amounts of
dependence within pre-specified time intervals of bounded
length. This is an important practical step forward from
requiring complete independence of execution times be-
tween successive jobs of the same task. Our main result
does not require the scheduler to know the execution time
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